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Single-Nuclei RNA-Seq on Human Retinal Tissue Provides Improved Transcriptome Profiling

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Single-Nuclei RNA-Seq on Human Retinal Tissue Provides Improved Transcriptome Profiling ARTICLE https://doi.org/10.1038/s41467-019-12917-9 OPEN Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling Qingnan Liang 1,2,3,9, Rachayata Dharmat1,2,8,9, Leah Owen4, Akbar Shakoor4, Yumei Li1, Sangbae Kim1, Albert Vitale4, Ivana Kim4, Denise Morgan4,5, Shaoheng Liang 6, Nathaniel Wu1, Ken Chen 6, Margaret M. DeAngelis4,5,7* & Rui Chen1,2,3* Single-cell RNA-seq is a powerful tool in decoding the heterogeneity in complex tissues by 1234567890():,; generating transcriptomic profiles of the individual cell. Here, we report a single-nuclei RNA- seq (snRNA-seq) transcriptomic study on human retinal tissue, which is composed of mul- tiple cell types with distinct functions. Six samples from three healthy donors are profiled and high-quality RNA-seq data is obtained for 5873 single nuclei. All major retinal cell types are observed and marker genes for each cell type are identified. The gene expression of the macular and peripheral retina is compared to each other at cell-type level. Furthermore, our dataset shows an improved power for prioritizing genes associated with human retinal dis- eases compared to both mouse single-cell RNA-seq and human bulk RNA-seq results. In conclusion, we demonstrate that obtaining single cell transcriptomes from human frozen tissues can provide insight missed by either human bulk RNA-seq or animal models. 1 HGSC, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA. 2 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston 77030 TX, USA. 3 Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, USA. 4 Department of Ophthalmology and Visual Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. 5 Department of Pharmacotherapy, the College of Pharmacy, University of Utah, Salt Lake City, UT 84132, USA. 6 Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 7 Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA. 8Present address: St. Jude Children’s Research Hospital, 262 Danny Thomas Pl, Memphis, TN 38105, USA. 9These authors contributed equally: Qingnan Liang, Rachayata Dharmat. *email: [email protected]; [email protected] NATURE COMMUNICATIONS | (2019) 10:5743 | https://doi.org/10.1038/s41467-019-12917-9 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-12917-9 he retina is a heterogeneous tissue and is composed of Using the snRNA-seq approach, a total of 5873 nuclei are Tmultiple neuronal and non-neuronal cell types1. In the profiled from both the peripheral and macular region of three human retina, there is an ordered array of ~70 different frozen human donor retina samples. Through unsupervised cell types across five major neuron classes: photoreceptors (rods clustering of the gene expression profiles, clusters corresponding and cones), retinal ganglion cells (RGCs), horizontal cells (HC), to all seven major cell types in the human retina (rod, cone, MG, bipolar cells (BC), amacrine cells (AC), and a non-neuronal HC, AC, BC, and RGC) are identified. Differentially expressed Müller glial cell (MG), each playing a unique role in processing genes from each cell type are obtained. We compare the gene visual signals1,2. The transcriptome of the human retina has been expression profile between macular and peripheral region for reported using bulk tissue RNA-seq3,4, and the overall gene each cell types. Significantly higher expression of mitochondrial- expression profiles from different retinal regions (macular and electron transport genes is found in macular rod cells compared peripheral region) were compared to each other5. These studies to the expression of the peripheral ones, which may indicate that provided general transcriptomic information of the retina as a comparatively higher levels of oxidation stress exists in the whole tissue, but they could not reveal the entirety of the retina’s macular, providing a potential explanation of higher vulnerability complexity because it lacks individual cell-type resolution. In of macular rod cells during aging. In addition, as expected, addition, transcriptomic studies of selected cell types of the compared to the published mouse single-cell data, the single- human and primate retina were performed but were not sufficient nuclei human data show stronger predictive power in prioritizing in obtaining the complete profile of all major cell types6,7. The genes associated with human disease. Finally, we find that pho- profiles of individual cell types, particularly rare types that toreceptor DEGs significantly enrich inherited retinal disease account for a small portion of the retina, will offer important (IRD) genes, indicating that they can serve as a prioritization tool insights to the scientific knowledge of biology and disease. For for novel disease gene discovery and cell-specific pathway ana- example, particular cell types, such as the cone cells in the cone- lysis. Overall, our study reports a transcriptome profile of all rod dystrophy (CRD) and the retinal ganglion cells in glaucoma, major cell types of the human healthy retina at the resolution of are the first targets of the diseases8,9. However, both cell types are the individual cell, which would serve as a rich resource for the found in low proportions in the human retina and their tran- scientific community. scriptome profiles have not been well studied. Given the great benefit of obtaining the transcriptome at the individual cell type or at the individual cell level, single-cell RNA-seq on human Results retina tissue is an area of great interest. The generation of the snRNA-seq data of human retina.To Recently, single-cell RNA-seq studies have been performed on generate transcriptome profiles for human photoreceptor cells, mouse retina, both within the whole retina10 and within specifi- retinae from three separate, healthy donors were obtained (n = 3 cally sorted cell types11,12. These studies provided unprecedent- donors). All three donors were Caucasian, ages between 60 and edly high-resolution transcriptomic data of each cell types and 80 years old (Table 1), and were thoroughly examined as pre- allowed for novel cell subtype discovery. However, usage of viously described in the methods. Figure 1 shows an example of mouse datasets could be limiting given the considerable differ- the donor tissues used for this study. There was no visible ences between the human and mouse retina. For example, the pathogenic indication found, not even macular drusen, a hall- mouse retina lacks the macula region of the retina that is found in mark of age-related macular degeneration commonly found in humans and primates13,14, a structure that is essential for both this age group, according to the fundus images15. Two-sample high visual acuity and color vision perception in the retina. punches from each retina (n = 6), one from the macula region Mouse cone cells are also different from those of humans in their and the other from the peripheral region, were collected and wavelength-sensitive opsin expression patterns. Thus, we propose subjected to single-cell nuclei RNA-Seq. After dispensing, nano- that single-cell transcriptomic study on human retinal tissues will wells were imaged and only wells with single nuclei were selected. expand our knowledge of the retina and become a rich resource cDNA library construction and sequencing were performed for a for related research, such as human disease-related studies. total of 6542 individual nuclei. Distribution of the number of Unlike model-organism-based studies, more factors are nuclei from each sample is listed in Table 2. To exclude low- needed to be taken into consideration for human tissue studies quality data, several QC steps were conducted (described in the in order to provide reliable results. One of the major concerns methods). As a result, 669 nuclei were filtered out, leaving a total in profiling the transcriptome of post-mortem human tissues is number of 5873 nuclei for downstream analysis. On average, RNA integrity. This issue worsens in single-cell-level studies 31,186 mapped reads were obtained per nucleus, with the median because the dissociation of tissue occurs for an extended period number of genes detected at 1044. To further evaluate the quality of time after the retina is dissected. Thus, the dissociation itself of snRNA-Seq data, bulk RNA-seq from the corresponding could also lead to changes in transcription due to damage of the sample was performed. Good correlation between the bulk gene retina that might have occurred during the waiting period. expression (FPKM, paired-end seq) and single-nuclei gene Another concern is the health condition of the human tissue, expression (average of normalized read count after transforma- since studies using multiple individuals with differing health tion and 3′ end seq, see methods) was observed with positive conditions could potentially add complexity in proper inter- correlation coefficient ranges from 0.66 to 0.71 (all genes with pretation of the data. Here, we report a single-cell tran- non-zero expression were used with gene numbers ranging from scriptomic study on healthy human retina tissues using snRNA- 12163 to 13657, among six samples. Spearman correlation coef- seq. We tackle the potential issues by two approaches. The first ficient was used). consisted of using snRNA-seq instead of single-cell RNA-seq (scRNA-seq) to profile tissues confirmed as healthy by a strict Table 1 Medical information of the sample donors. post-mortem phenotyping. The second approach involved fl snRNA-seq, where tissues were ash-frozen immediately after Donor number Globe Age Sex Race dissection to preserve RNA integrity, minimizing the variation 12–887 OS (left eye) 78 F Caucasian due to differences in tissue dissociation conditions.
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